1. Salience and Default Mode Network Dysregulation in Chronic Cocaine Users Predict Treatment Outcome This study is to identify multimodal imaging measures that predict treatment outcome of cocaine addiction. We investigated consequences of structural differences on resting-state functional connectivity (rsFC) in cocaine addiction and tested whether rsFC of the identified circuits predict relapse in an independent cohort. Subjects included 64 non-treatment-seeking cocaine users (NTSCUs) and 67 healthy controls (HCs) and an independent treatment-completed cohort (n=45) of cocaine dependent individuals scanned at the end of a 30-day residential treatment program. Differences in cortical thickness and related rsFC between NTSCUs and HCs were identified. Survival analysis, applying cortical thickness of the identified regions, rsFC of the identified circuits and clinical characteristics to the treatment cohort, was used to predict relapse. Lower cortical thickness in bilateral insula and higher thickness in bilateral temporal pole (TP) were found in NTSCUs versus HCs. Whole brain rsFC analyses with these four different anatomical regions as seeds revealed 8 weaker circuits including within the salience network (insula seeds) and between TP and elements of the default mode network in NTSCUs. Applying these circuits and clinical characteristics to the independent cocaine dependent treatment cohort, functional connectivity between right TP and medial prefrontal cortex (mPFC), combined with years of education, predicted relapse status at 150 days with 88% accuracy. Deficits in the salience network suggest an impaired ability to process physiologically salient events, while abnormalities in a TP-mPFC circuit might speak to the social-emotional functional alterations in cocaine addiction. The involvement of the TP-mPFC circuit in a model highly predictive of relapse highlight the importance of social-emotional functions in cocaine dependence, and provide a potential underlying neural target for therapeutic interventions, and for identifying those at high risk of relapse. (Geng et al., Brain, 2017) 2. Regional Excitation-Inhibition Balance Predicts Default-Mode Network Deactivation via Interregional Functional Connectivity This study is to investigate the relationship between regional neurotransmitter (glutamate and GABA) levels, interregional functional connectivity, and task-induced brain activation. The default mode network (DMN) has shown deactivation in response to tasks demanding external attention and impaired DMN deactivation has been demonstrated in aged population and in various neuropsychiatric disorders, suggesting a critical role of DMN deactivation in brain functions. The neural mechanism underlying this observation, however, is still largely unknown. As the coordination of regional neurochemical substrates and interregional neural interactions are both essential for normal brain functioning, a quantitative description of how they impact on the DMN deactivation may provide new insights into the mechanism. We assessed task-induced deactivation, interregional functional connectivity and regional excitation-inhibition balance (evaluated by glutamate/GABA concentration ratio) in the posterior cingulate cortex/precuneus (PCC/PCu) region of the DMN, and further examined the triple-relationship among these measures. We found that greater task-induced PCC/PCu deactivation was associated with i) lower concentration ratio of glutamate to GABA measured from this region, and ii) stronger intra-DMN connection and antagonistic interactions between DMN and two other large-scale networks: executive control network and salience network (SN); meanwhile the PCC/PCu SN connection strength was associated with the excitation-inhibition balance at the PCC/PCu. Further mediation analyses revealed that the PCC/PCu SN functional interactions partially mediated the relationship between task-induced deactivation and the neurotransmitter levels at PCC/PCu. The triple-relationship discovered in the present study has the potential to bridge DMN-deactivation related findings from various neuroimaging modalities, and may provide new insights into the neural mechanism of DMN deactivation. A manuscript was submitted for publication, and reanalyses of the data were done based on comments from reviewers. (Manuscript submitted for publication) 3. Graph theory reveals amygdala modules consistent with its anatomical subdivisions Similarities in the cellular and neurochemical composition of the amygdaloid subnuclei suggests their clustering into subunits that may exhibit unique functional organization. The topological principal of community structure, on the other hand, has been used to identify functional subnetworks, in neuroimaging data, that reflects the brain effective organization. Here we used the principle of modularity to investigate the modular organization of the amygdala using resting state functional magnetic resonance imaging (rsfMRI) data. We found that modularity analysis identified subnetworks consistent with the main anatomical subdivisions of the amygdala that embody relevant functional and structural properties. Additionally, functional connectivity pathways of these subunits, and their correlation with task-induced amygdala activation, revealed distinct functional profiles consistent with the neurobiology of the amygdala nuclei. These modularity findings corroborate the structurefunction relationship between amygdala anatomical substructures, supporting the use of network analysis techniques to generate biologically meaningful partitions of brain structures. A manuscript was submitted for publication, and reanalyses of the data were done based on comments from reviewers. (Submitted for publication) 4. Trait impulsivity is distinctively associated with functional connectivity of ventral striatum circuits in smokers versus nonsmokers This study is to investigate neural circuits that are associated with trait impulsivity in smokers and nonsmokers. Impulsivity is a multi-facet trait and high impulsivity is often observed in individuals with substance abuse disorder (SUD) including nicotine addiction. Ventral striatum (VS) is a key structure implicated in impulsivity, and its interactions with other brain regions might modulate impulsive behaviors. In this study, we used resting state functional connectivity (rsFC) to investigate the association between impulsivity and intrinsic connectivity of VS circuits, and the potential alterations in smokers versus nonsmokers. Sixty smokers and 60 matched nonsmokers underwent resting-state functional MRI (fMRI) scans and their impulsivity was assessed. Voxel-wise rsFC between bilateral VS and all other brain regions were computed for each subject. Significant interactions were found in the dorsal anterior cingulate cortex (dACC) and bilateral amygdala. Specifically, significant positive correlation between impulsivity and rsFC of VS-amygdala circuit was found in smokers but not in nonsmokers, whereas significant positive correlation between impulsivity and rsFC of VS-dACC circuit was found in nonsmokers but not smokers. To further examine functional roles of these brain circuits in impulsivity, a subset of the participants underwent fMRI scans while performing Go/NoGo and emotional memory tasks. VS-amygdala connectivity positively correlated with the activation in the amygdala (negative vs. positive condition); and VS-dACC connectivity positively correlated with the activation in the dACC during failed inhibition (losing impulsive control). These results provide novel evidence supporting the notion that the striatal-frontal circuits are involved in impulse control, while striatal-limbic circuits in impulse drive. (Manuscript in preparation)